Microtheories for SDI - Accounting for diversity of local conceptualisations at a global level

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.The categorization and conceptualization of geographic features is fundamental to cartography, geographic information retrieval, routing applications, spatial decision support and data sharing in general. However, there is no standard conceptualization of the world. Humans conceptualize features based on numerous factors including cultural background, knowledge, motivation and particularly space and time. Thus, geographic features are prone to multiple, context-dependent conceptualizations reflecting local conditions. This creates semantic heterogeneity and undermines interoperability. Standardization of a shared definition is often employed to overcome semantic heterogeneity. However, this approach loses important local diversity in feature conceptualizations and may result in feature definitions which are too broad or too specific. This work proposes the use of microtheories in Spatial Data Infrastructures, such as INSPIRE, to account for diversity of local conceptualizations while maintaining interoperability at a global level. It introduces a novel method of structuring microtheories based on space and time, represented by administrative boundaries, to reflect variations in feature conceptualization. A bottom-up approach, based on non-standard inference, is used to create an appropriate global-level feature definition from the local definitions. Conceptualizations of rivers, forests and estuaries throughout Europe are used to demonstrate how the approach can improve the INSPIRE data model and ease its adoption by European member states

Automatic Document Summarization Using Knowledge Based System

This dissertation describes a knowledge-based system to create abstractive summaries of documents by generalizing new concepts, detecting main topics and creating new sentences. The proposed system is built on the Cyc development platform that consists of the world’s largest knowledge base and one of the most powerful inference engines. The system is unsupervised and domain independent. Its domain knowledge is provided by the comprehensive ontology of common sense knowledge contained in the Cyc knowledge base. The system described in this dissertation generates coherent and topically related new sentences as a summary for a given document. It uses syntactic structure and semantic features of the given documents to fuse information. It makes use of the knowledge base as a source of domain knowledge. Furthermore, it uses the reasoning engine to generalize novel information. The proposed system consists of three main parts: knowledge acquisition, knowledge discovery, and knowledge representation. Knowledge acquisition derives syntactic structure of each sentence in the document and maps words and their syntactic relationships into Cyc knowledge base. Knowledge discovery abstracts novel concepts, not explicitly mentioned in the document by exploring the ontology of mapped concepts and derives main topics described in the document by clustering the concepts. Knowledge representation creates new English sentences to summarize main concepts and their relationships. The syntactic structure of the newly created sentences is extended beyond simple subject-predicate-object triplets by incorporating adjective and adverb modifiers. This structure allows the system to create sentences that are more complex. The proposed system was implemented and tested. Test results show that the system is capable of creating new sentences that include abstracted concepts not mentioned in the original document and is capable of combining information from different parts of the document text to compose a summary

Adjectival forms in Middle English: syntactic and semantic implications.

[Abstract] Our main purpose in this paper is to look into the place of adjectives in a particular period in the history of English as regards their position in the Noun Phrase and whether such position may somehow alter the meaning of the adjective and of the NP itself. To this end, only adjectives in an attributive function both as premodifiers or postmodifiers of the head will be considered. In section 1 we will briefly attempt to draw a line between the class “adjective” and other morphological classes considering different viewpoints. Section 2 will be devoted to the consideration of word-order as one of the factors characterising adjectives inside the NP and how their position may alter the meaning of the whole phrase. The next step in our research will be embodied in section 3 where we will present the corpus material for our study taken from the Middle English part of the Helsinki Corpus of English Texts and section 4 will provide the analysis of the data obtained from our evidence. Section 5 will finally supply our conclusions. We will attempt —if possible— to find an explanation grounded on syntactic and semantic criteria for the different shades of meaning found to depend on position

A representação da semântica dos adjectivos em ontologias jurídicas: informação importante ou secundária?

Este trabalho apresenta algumas conclusões de uma dissertação de mestrado. O tema principal deste artigo é a semântica dos adjetivos do domínio jurídico. Duas questões embasaram essa pesquisa: “por que representar a semântica dos adjetivos em uma ontologia jurídica?” e “como representá-la?”. Em primeiro lugar, nós fazemos uma comparação entre léxicos e ontologias jurídicos e de língua geral. Em segundo lugar, apresentamos a construção do corpus, a análise dos adjetivos e algumas sugestões de codificação dos adjetivos no editor de ontologias Protégé

The place(s) of pain and its linguistic descriptions - the morphology and lexico-semantics of English pain descriptors : a cognitive linguistic perspective

This paper aims at identifying the place of pain in language by analysing, in most part, adjectival pain descriptors (in terms of their morphology and lexico-semantics), especially the ones present in the English (original) version of the McGill Pain Questionnaire (Melzack & Torgerson 1971, Melzack 1975), mainly through the cognitive linguistic prisms. This self-report questionnaire (given by doctors to their patients so that the latter can describe their pain in terms of various qualities and intensity) has for years been successfully employed in clinical settings, but its diagnostic potency may be to some extent compromized by the interplay of both linguistic and extra-linguistic factors. Thus, in order to check how potent these MPQ descriptors are (and whether they are still potent), the present analysis is enriched with the discussion of these adjectival pain collocations not only in the context of the MPQ, but also in other ‘localizations’, be it an alternative pain questionnaire, and fragments of academic articles and books addressing certain types/ qualities of pain. Adopting such an approach provides the chance to glimpse the pain descriptors in question in the broader context, that is, how pain is ‘located’ in the academic discourse of pain experts and clinicians, but also, and perhaps even more importantly, how ‘lay’ pain sufferers ‘position’ their pain(s). The analysis carried out and the conclusions drawn reveal an interesting ‘place’—a point of convergence, an intersection of pain (as a multi-layered construct) and metaphorinfused language. My conviction, then, is that pain is placed in and predominantly expressed via metaphoric language at various (less and more subtle) levels, and also that pain metaphor is not only a research object, but may additionally prove an efficient (diagnostic) research tool

Knowledge modeling of phishing emails

This dissertation investigates whether or not malicious phishing emails are detected better when a meaningful representation of the email bodies is available. The natural language processing theory of Ontological Semantics Technology is used for its ability to model the knowledge representation present in the email messages. Known good and phishing emails were analyzed and their meaning representations fed into machine learning binary classifiers. Unigram language models of the same emails were used as a baseline for comparing the performance of the meaningful data. The end results show how a binary classifier trained on meaningful data is better at detecting phishing emails than a unigram language model binary classifier at least using some of the selected machine learning algorithms

Two set-theoretic approaches to the semantics of adjective-noun combinations

This work addresses the problem of adjective-noun combinations. Conventionally, adjectives belong to a hierarchy. This has the consequence that a uniform treatment of adjectives is unattainable---without resorting to notions such as possible worlds, which are difficult to map into competent computer programs. In this work, we propose two set-theoretic approaches to the semantics of adjective-noun combinations. The first hypothesizes that an adjective-noun compound is a subset of its constituent noun. The second hypothesizes that the adjective-noun combinations can semantically be thought of as a set intersection involving the adjective(s) and the head noun of the compound. This work argues that the class of adjectives known as privative can be accommodated within an existing class in the adjective hierarchy, known as subsective . This step is important for the provision of uniform treatments of adjective-noun combinations. The two approaches make use of types, both for gaining a finer granularity of analysis and for imposing structure on the problem domain. It is shown that the mixture of a typing system with set theory provides promising results that are manifested in the provision of compositional solutions to the adjective-noun combinations. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .A24. Source: Masters Abstracts International, Volume: 43-01, page: 0229. Adviser: Richard Frost. Thesis (M.Sc.)--University of Windsor (Canada), 2004

Non-predicating adjectives: a semantic account

This thesis provides a semantic account of non-predication in the adjectives of English. Particular attention is paid to adjectives that are only non-predicating when they modify certain types of nouns; both agentive nouns and degree nouns are decomposed semantically into two distinct semantic elements, one of which consists of the referent (referential element) and another which consists of either an action associated with the noun or a quality already expressed by it (non-referential element). The other main focus of the thesis is denominal adjectives which have a structure like that of modifying nouns and which are differentiated from regular quality attributing adjectives via their semantic structure that does not express a single quality. The semantics of regular predicating adjectives is discussed, and it is found that predication requires an adjective to attribute a quality directly to the noun referent. Adjectives which have a function that does not meet this description are then restricted to the attributive (prenominal position). It is suggested that the prenominal position allows for a greater variety of semantic behaviours due to the relationship between the two phrasal elements not being made explicit

Distributional Semantic Models of Attribute Meaning in Adjectives and Nouns

Hartung M. Distributional Semantic Models of Attribute Meaning in Adjectives and Nouns. Heidelberg: Universität Heidelberg; 2015